Biology subjects

Li, C.-S. R.

Publications and source records attributed to Li, C.-S. R..

5 recordsLinked to original sources

bioRxiv2026

Disrupted Higher-Order Topology in OCD Brain Networks Revealed by Hodge Laplacian - an ENIGMA Study

Brain disorders are increasingly understood as disorders of distributed brain circuits, yet functional connectivity (FC), the dominant framework for mapping them, treats the brain as a collection of pairwise relationships between regions and cannot represent pathology distributed across coordinated sets of connections. We introduce a Hodge-Laplacian topological framework that localizes higher-order "loop" (1-cycle) organization within functional connectome, maps each loop to specific edges and networks, and yields a subject-level measure of loop expression. Applied to resting-state fMRI from the ENIGMA-OCD consortium (1,024 patients and 1,028 controls across 28 sites), the framework identified 93 loop-level abnormalities in obsessive-compulsive disorder (OCD), concentrated in frontoparietal and somatomotor systems. The edges forming these loops largely showed no significant differences between groups, indicating that the abnormalities were invisible to conventional FC analysis. The frontoparietal and somatomotor loop clusters recurred across the clinical subgroups, suggesting convergence on a shared higher-order phenotype. Robustness analyses showed the loop signal reflected higher-order organization rather than an artifact of individual edges, the network backbone, or any single site. These results indicate that coordinated, multi-edge pathology exists and can be localized even when pairwise analyses fail to detect it, positioning higher-order topology as a generalizable axis for mapping circuit pathology across psychiatric and neurological disorders.

neuroscience↗

bioRxiv2025

Functional Inputs to the Subgenual Cingulate Cortex Distinguish Neurotypical Individuals with Severe and Mild Depressive Problems: Granger Causality and Clustering Analyses

Extant research has implicated functional connectivity of the subgenual anterior cingulate cortex (sgACC) in major depressive disorders or depressive traits in neurotypical populations. However, prior studies have not distinguished the inputs and outputs of the sgACC, and the "diagnostic" accuracy of these connectivity metrics remains elusive. Here, we analyzed data of 890 subjects (459 women, age 22 to 35) from the Human Connectome Project using Granger causality analyses (GCA) with the sgACC as the seed and 268 regions of interest from the Shens atlas as targets. Individual connectivities were assessed with an F test and group results were evaluated with a binomial test, both at a corrected threshold. We identified brain regions with significant input to and output from the sgACC. Clustering analyses of Granger causality input, but not Granger causality output or resting state connectivity features revealed distinct subject clusters, effectively distinguishing individuals with severe and mild depressive symptoms and those with comorbidities. Specifically, weaker projections from the fronto-parietal and orbitofrontal cortices, anterior insula, temporal cortices, and cerebellum to the sgACC characterized five clusters with low to high scores of depression as well as comorbid internalizing and externalizing problems. Machine learning using a logistic classifier with the significant "GCA-in" features and 5-fold cross-validation achieved 87% accuracy in distinguishing subject clusters, including those with high vs. low depression. These new findings specify the functional inputs and outputs of the sgACC and highlight an outsized role of sgACC inputs in distinguishing individuals with depressive and comorbid problems. Significance StatementDepression affects millions worldwide. Understanding the neural mechanisms would facilitate treatment of depression. In this study, we investigated how different parts of the brain send signals to and/or receive signals from a key brain region - subgenual cingulate cortex - implicated in the pathophysiology of depression. Using brain scans from nearly 900 adults, we found that weaker signals coming into this area, especially from regions involved in thinking and emotion, were linked to higher levels of depression and other behavioral problems such as anxiety and aggression. These findings help us better understand how regional communications in the brain relate to emotional well-being and may support new ways to identify and treat people with a depressive disorder.

neuroscience↗

bioRxiv2024

Hypothalamic connectivities and self-evaluated aggression in young adults

IntroductionThe hypothalamus plays a pivotal role in supporting motivated behavior, including aggression. Previous work suggested differential roles of the medial hypothalamus (MH) and lateral hypothalamus (LH) in aggressive behaviors, but little is known about how their resting-state functional connectivity (rsFC) may relate to aggression in humans. MethodsWe employed the data from the Human Connectome Project (HCP) and examined the rsFCs of LH and MH in 745 young adults (393 women). We also explored sex differences in the rsFCs. We processed the imaging data with published routines and evaluated the results of voxel-wise regression on aggression score, as obtained from Achenbach Adult Self Report, with a corrected threshold. ResultsThe analysis revealed significant rsFC between the LH and clusters in the middle temporal and occipital gyri across all subjects and in the thalamus for men, both in negative correlation with aggression score. Slope test confirmed sex differences in the correlation between LH-thalamus rsFC and aggression score. No significant rsFC was observed for MH. ConclusionsThese findings suggest a role of LH rsFCs and sex differences in LH-thalamus rsFC in the manifestation of aggression in humans. The findings highlight the need for further research into sex-specific neural pathways in aggression and other related behavioral traits of importance to mental health.

neuroscience↗

bioRxiv2024

Polygenic risk for depression and resting state functional connectivity of subgenual anterior cingulate cortex in young adults

Genetic variants may confer risks for depression by modulating brain structure and function. Prior evidence has underscored a key role of the subgenual anterior cingulate cortex (sgACC) in depression. Here, we built on the literature and examined how the resting state functional connectivity (rsFC) of the sgACC was associated with polygenic risks for depression. We followed published routines and computed seed-based whole-brain sgACC rsFC and polygenic risk scores (PRS) of 717 young adults curated from the Human Connectome Project. We performed whole-brain regression against PRS and severity of depression symptoms in a single model for all subjects and for men and women alone, controlling for age, sex (for all), race, severity of alcohol use, and household income, and evaluated the results at a corrected threshold. We found lower sgACC rsFC with the default mode network and frontal regions in association with PRS and lower sgACC-cerebellar rsFC in association with depression severity. We also noted sex differences in the connectivity correlates of PRS and depression severity. In an additional set of analyses, we observed a significant correlation between PRS and somatic complaints score and altered sgACC-somatosensory cortical connectivity in link with the severity of somatic complaints. Our findings collectively highlighted the pivotal role of distinct sgACC-based networks in the genetic predisposition to depression and the clinical manifestation of depression. Distinguishing the risk from severity markers of depression may have implications in developing early and effective treatments for individuals at risk for depression.

neuroscience↗

bioRxiv2022

Appetitive and aversive cue reactivities differentiate biotypes of alcohol drinkers

Craving reflects the subjective urge to use drugs and can be triggered by both positive and negative emotional states. However, no studies have systematically investigated the relative roles of these mechanisms in the pathophysiology of substance misuse or distinguished the mechanisms in individual vulnerability to substance use disorders. In the current study, we performed meta-analyses of drug cue-elicited reactivity and win and loss processing in the monetary incentive delay task to identify distinct neural correlates of appetitive and aversive responses during cue exposure. We then characterized the appetitive and aversive cue responses in seventy-six alcohol drinkers performing a cue craving task during fMRI. Imaging data were processed according to published routines. The appetitive circuit involved medial cortical regions and the ventral striatum, and the aversive circuit involved the insula, caudate and mid-cingulate cortex. We observed a significant correlation of {beta} estimates of cue-elicited activity of the appetitive and aversive circuit. However, individuals varied in appetitive and aversive cue responses. From the regression of appetitive (y) vs. aversive (x) {beta}, we identified participants in the top 1/3 each of those with positive (n = 15) and negative (n = 11) residuals as "approach" and "avoidance" biotype, with the others as the "mixed" biotype (n = 50). For clinical characteristics, the avoidance biotype showed higher sensitivity to punishment. In contrast, the approach biotype showed higher levels of sensation seeking and alcohol expectancy for social and physical pressure. The findings highlighted distinct neural underpinnings of appetitive and aversive components of cue-elicited reactivity and substantiated the importance of biotyping substance misuse.

neuroscience↗